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DBMS > Apache Druid vs. Apache Impala vs. Databricks vs. Spark SQL vs. SwayDB

System Properties Comparison Apache Druid vs. Apache Impala vs. Databricks vs. Spark SQL vs. SwayDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonSpark SQL  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic DBMS for HadoopThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Spark SQL is a component on top of 'Spark Core' for structured data processingAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument store
Relational DBMS
Relational DBMSKey-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitedruid.apache.orgimpala.apache.orgwww.databricks.comspark.apache.org/­sqlswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmldocs.databricks.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksApache Software FoundationSimer Plaha
Initial release20122013201320142018
Current release29.0.1, April 20244.1.0, June 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2commercialOpen Source infoApache 2.0Open Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++ScalaScala
Server operating systemsLinux
OS X
Unix
LinuxhostedLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyesnono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementswith Databricks SQLSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBCPython
R
Scala
Java
Python
R
Scala
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factoryesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonononoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnono
More information provided by the system vendor
Apache DruidApache ImpalaDatabricksSpark SQLSwayDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache DruidApache ImpalaDatabricksSpark SQLSwayDB
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